---
datasets:
- openagi-project/OpenAGI-set-dpo-v0.1
base_model: freecs/ThetaWave-7B-v0.1
license: apache-2.0
---

# OpenAGI-7B-v0.1

DPO tuned on a small set of GPT4 generated responses.

Give it a try:
```python
from transformers import AutoModelForCausalLM, AutoTokenizer

device = "cuda"  # the device to load the model onto

model = AutoModelForCausalLM.from_pretrained("openagi-project/OpenAGI-7B-v0.1")
tokenizer = AutoTokenizer.from_pretrained("openagi-project/OpenAGI-7B-v0.1")

messages = [
    {"role": "user", "content": "Who are you?"},
]

encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")

model_inputs = encodeds.to(device)
model.to(device)

generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
decoded = tokenizer.batch_decode(generated_ids)
print(decoded[0])
```

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 |- [GR](https://twitter.com/gr_username)


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